GeaBase: A High-Performance Distributed Graph Database for Industry-Scale Applications

Graph analytics have been gaining tractions rapidly in the past few years. It has a wide array of application areas in the industry, ranging from e-commerce, social network and recommendation systems to fraud detection and virtually any problem that requires insights into data connections, not just data itself. In this paper, we present GeaBase, a new distributed graph database that provides the capability to store and analyze graph-structured data in real-time at massive scale. We describe the details of the system and the implementation, including a novel update architecture, called Update Center (UC), and a new language that is suitable for both graph traversal and analytics. We also compare the performance of GeaBase to a widely used open-source graph database Titan. Experiments show that GeaBase is up to 182x faster than Titan in our testing scenarios. We also achieves 22x higher throughput on social network workloads in the comparison.